How to fact-check AI answers without checking everything

Llama writes fluent, confident answers whether it is right or wrong. Most of the time the broad picture is fine; the trouble hides in the details: a date off by a year, a quote nobody ever said, a rule that has changed, a book that does not exist. You do not need to verify everything. You need a quick way to decide what to check and how to check it. Here it is.

Know where errors cluster

Some kinds of content go wrong far more often than others. Treat these as "check before use":

• Exact numbers: statistics, prices, measurements, percentages.
• Dates and the order of events.
• Quotes attributed to real people.
• Citations: books, papers, articles, page numbers, links. Models often invent references that look completely real.
• Anything recent. According to Meta's model cards, Llama 4's training data ends in August 2024 and Llama 3.x's in December 2023. Our chat cannot browse, so newer events, prices, laws and software versions are unknown to it.
• Niche facts: small towns, less famous people, local rules.
• Health, legal and financial specifics, where a mistake costs the most.

Broad explanations of well-documented topics, such as how photosynthesis works or what a mortgage is, are generally more reliable, though still not guaranteed.

A five-step routine

1. Decide the stakes. A birthday poem needs no checking. A figure going into a report, a question about medicine or a legal deadline does. Spend effort in proportion.
2. Pull out the claims. Ask Llama to list them for you (prompt below). A list is much easier to check than a paragraph.
3. Check each claim against a primary source: the official website, the original study, the law itself, the company's documentation. A second AI answer is not a source.
4. Check the date. Is your source current? Could anything have changed after the model's cut-off?
5. Fix or drop. Correct what is wrong. If you cannot confirm a claim, remove it or mark it as unverified.

Go back over your last answer. Pull out each statement of fact
(names, dates, numbers, quotes, rules) and put them in a table with
three columns: the statement, how sure you are of it (sure / fairly
sure / guessing), and where I could look it up. Add nothing new.

The model's own rating of how sure it is is only a hint, since it can be wrong with full confidence, but it helps you decide where to start. Open the fact-table prompt in the chat after any answer you need to verify.

Ask in a way that makes checking easier

Weak:
What are the rules for renting out my flat short-term?

Strong:
Give me a general overview of the kinds of rules that often apply
to short-term rentals (registration, taxes, building rules,
insurance). Don't state specific laws or amounts for my city; instead
tell me which official offices or documents I should check and what
to ask them. I live in [country / city].

The strong version plays to what Llama does well (structure, explanation, checklists) and sends you to the authoritative source for the details that vary from place to place and year to year.

Other habits that help:

• Give it the source. Paste the article, contract or documentation and write "answer only from this text and quote the sentence you rely on". Then check each quote against the original.
• Invite uncertainty. "If you don't know, say so" makes an honest "I'm not sure" more likely.
• Separate facts from opinion. "Mark which parts are established facts and which are interpretation."

Checking citations and quotes

When an answer names a book, paper or article, look it up by its precise title in a library catalogue, a scholarly search engine or on the publisher's site. If you cannot find it, assume it does not exist. If it does exist, open it and confirm that it says what the answer claims, because a real paper can still be described wrongly. For quotes, find the original speech, interview or text; collections of quotes on the web are full of misattributions too.

For schoolwork or anything you publish, never cite a source you have not read yourself.

A better way to use Llama with sources is the other way round: find the sources yourself, paste the relevant passages, and ask Llama to compare, explain or summarise them.

Below are two passages from different reports on the same topic. Where do they agree, where do they disagree, and which statements in each are claims I should verify further? Quote the exact sentences. Passage A: [paste] Passage B: [paste]

Because every statement in the answer can be traced back to a quote you supplied, checking it takes minutes rather than an afternoon.

Checking what Llama reads in images

Llama 4 Maverick and Llama 4 Scout can read photos and screenshots, but small print, handwriting, poor lighting and busy charts invite misreadings. When the model extracts numbers or text from an image, compare a few values with the original by eye. Ask it to "mark anything you are unsure of with (?)" so doubtful readings stand out.

Red flags in an answer

• Very precise figures with no source given.
• A quote that sounds a little too neat for the person it is attributed to.
• Specific article numbers, deadlines or amounts from laws in your country.
• References with perfect-looking details that you cannot find anywhere.
• Claims about "the latest" version, price or event. The model's "latest" is frozen at its cut-off.
• Facts that change when you regenerate. On important questions, regenerate once or twice; if the details shift between versions, treat all of them as unverified.

Where to check

The summarizer helps you get through long sources faster: summarise the official document, then read the parts that matter in the original. To understand why errors happen in the first place, read how large language models work, and for safe habits with sensitive topics see AI privacy and safety.

FAQ

How often is Llama wrong?

There is no single number. It depends on the topic, the model, how the question is phrased and whether you provide source material. Assume any specific fact can be wrong until you have checked it.

Is a bigger model more accurate?

Larger models tend to know more facts, but every model makes mistakes and none of them knows about events after its cut-off. Checking matters for all four models in our chat. Comparing answers from Llama 4 Maverick and Llama 3.3 70B can show you where to look, but agreement between them is not proof.

Can Llama check a website for me?

No. It cannot open links. Copy the relevant text into the chat and ask about that instead.

Do I need to check answers about images too?

Yes. When Llama 4 describes a photo or reads text from a screenshot, it can misread small details or guess at blurry parts. Compare the key values with the image yourself before you rely on them.

Why did it apologise and change a correct answer?

Chat models are tuned to be agreeable, so pushing back can make them give way even when they were right. That is why outside sources, not the model's second opinion of itself, are the real test.